Analyzing Career Paths: How to Become a Data EngineerAnalyzing Career Paths: How to Become a Data EngineerAnalyzing Career Paths: How to Become a Data Engineer

Data has rapidly changed the world. Thanks to modern computing power, the ubiquity of the internet, and the emergence of smart devices, government agencies and businesses can collect massive amounts of data. This data has infinite applications — from determining the number of cars passing through an intersection to scrutinizing the clicking habits of a certain age group on a social media platform.

But data doesn’t magically appear on computers. Data scientists use special software to extract and analyze it and determine how a business or agency can best respond. Even everyday apps and programs rely on data to function and thus need specialized software created by data engineers. Data engineering is a highly specialized field that requires extensive knowledge, skills, and proficiency in computer science and information technology. Individuals interested in the field are likely to find that completing an advanced education program, such as Maryville University’s online Master’s in Data Science program, can help them toward their goal. Read on to discover more about how to become a data engineer.

Data engineers create the software and programming frameworks that manage data storage and manipulation by both internal data scientists and external users. If data scientists are astronauts riding the space shuttle and performing experiments in orbit, then data engineers are responsible for building the shuttle and getting the experiments into space. In the real world, what a data engineer does is more complex than an analogy. Data engineers work with data scientists and others responsible for creating a pipeline specifically built to leverage data for an organization. Using software and coding languages, data engineers design programs to draw data from various sources, sort it, and present it in concise reports that managers can interpret to make informed decisions. Data engineers also make systems designed to handle data search tools useful to consumers, businesses, and data scientists. For example, ride-sharing services need to access the data of every car in a specific area when a user requests a ride. Another example is a music service whose servers must have the capacity to stream millions of songs requested by millions of users at any given time. These types of services can perform their tasks thanks to data engineers.

Data engineers are instrumental in helping companies collect data and turn it into something useful. They are not only key to building and managing big data analytics programs and operations, but they ensure that data mining applications are repeatable, scalable, and impenetrable. The benefits of becoming a data engineer include the following:

Pursuing a high-level career as a data engineer requires specialized education, including an advanced degree and specific certification. Here are the steps to become a data engineer.

The first step toward becoming a data engineer is earning a bachelor’s degree in data science or a related field. Here, students learn how to collect, clean, and analyze data and then leverage their findings to prepare reports. They discover how to blend statistics and data technology to suit a wide variety of applications. In addition, they develop soft skills that will be crucial in their careers, including teamwork, communication, and critical thinking.

The best way to build on skills and knowledge learned in a classroom is on the job. Some bachelor’s degree programs may offer internships, and after graduating, students should seek opportunities to practice in professional settings. An entry-level data engineer can begin their career as an IT assistant to gain further mastery in programming computers, building data structures, maintaining databases, and designing software. Employers that use data engineers extensively include manufacturing companies, insurance agencies, technology companies, marketing firms, nonprofits, and government agencies.

Reaching senior-level data engineer status usually requires several years of building and managing intricate and secure data structures. They also can train junior hires and build infrastructures to mine and assess quality data that can direct business operations.

While a college degree provides a strong foundational knowledge, several professional certifications can further show prospective employers that job candidates are qualified to take on the responsibilities of advanced data engineering roles.

Oracle, Microsoft, Amazon, and other major technology companies offer certification courses and tests to ensure that data engineers have the requisite competencies. These certifications aren’t required to work in the field, but employers may consider them valuable.

After earning a bachelor’s degree, several options are available for advanced education. Many aspiring data engineers pursue an advanced degree, such as a online master’s in data science. These graduate programs often feature project-based coursework, with courses in machine learning, SQL databases, big data analytics, and more. As a result, the curriculum provides graduates with a well-rounded education in data science.

Education is one highly relevant factor in determining a data scientist’s salary. Those with a graduate-level degree in data science will find a plethora of job opportunities in lucrative sectors such as finance, insurance, professional services, and IT.

Individuals interested in pursuing data engineering jobs will be well-served by developing a variety of skills and proficiencies. Examples include analytical and communication skills, ingenuity, and attention to detail.

Data engineers not only need to know how to collect and sort data, they also must understand how to decode and interpret it. As such, professionals who understand how to analyze and draw conclusions from data are likely to have the best job prospects.

Professionals who choose this career path must be able to communicate highly technical information to nontechnical managers and staff. Individuals who develop strong written and verbal communication skills will be well prepared to relay complex information in a concise, easily digestible format.

Data engineers must be able to find new and innovative ways to solve problems. Professionals adept in out-of-the-box thinking will understand that solutions that don’t initially work as intended may still work upon further refinement.

The smallest programming errors can cause a project to fail. Consequently, data engineers must have finely attuned attention to detail.

The U.S. Bureau of Labor Statistics (BLS) includes data engineers in the category of computer and information research scientists. As of May 2019, this master’s-level group of careers had a median annual salary of $122,840. Pay for the lowest 10% of earners was less than $69,990, while the top 10% of earners was more than $189,780. Earnings potential can vary greatly based on a number of factors, including education and experience, industry, and job location.

Individuals interested in how to become a data engineer should know that this is a thriving field; the continued proliferation of data means the job market for data engineers should remain strong. The BLS projects the employment of computer and information research scientists will grow by 15% between 2019 and 2029, about three times faster than the average of all occupations. Growth in this field is expected to be driven by several factors, including an increased emphasis on cybersecurity, coupled with rapid growth in the number of businesses that want to collect, sort, and analyze data to help them better understand their consumer base.

Data engineers need to be tech-savvy, problem-solving experts who relish facing challenges and seeking optimal solutions. Are you ready to expand your knowledge and take your data engineering career to the next level? Discover how Maryville University’s online Master’s in Data Science can help prepare you for the job you want.

Recommended Reading

Why Are Data Scientists in High Demand?

The Future of Engineering: Staying in Step with Technology

Building Skills for the Future of Machine Learning

Sources

Capterra, “7 Big Data Certifications to Take Your Career to the Next Level”

CIO, “The Top 11 Big Data and Data Analytics Certifications for 2020”

O’Reilly, “Data Engineers vs. Data Scientists”

PayScale, Average Data Engineer Salary

Towards Data Science, “Data Engineering — A Complete Reference Guide from A-Z (2019)”

U.S. Bureau of Labor Statistics, Computer and Information Research Scientists

Xplenty, “Data Engineering: What Is a Data Engineer and How Do I Become One?”